Urinary bisphenol A and serum lipids: a meta-analysis of six NHANES examination cycles (2003-2014)

Urinary bisphenol A and serum lipids: a meta-analysis of six NHANES examination cycles (2003–2014)

Linda Dunder,  ¹ Margareta H Lejonklou, ¹ P Monica Lind, ¹ Lars Lind ²

To cite: Dunder L, Lejonklou MH, Lind PM, et al. J Epidemiol Community Health 2019;73:1012–1019.

► Additional material is published online only. To view please visit the journal online (http:// dx. doi. org/ 10. 1136/

jech- 2019- 212555).

1

Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden

2

Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden Correspondence to Linda Dunder, Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala university, Uppsala 75185, Sweden;

linda. dunder@ medsci. uu. se Received 23 April 2019 Revised 12 July 2019 Accepted 14 July 2019 Published Online First 24 September 2019

► http:// dx. doi. org/ 10. 1136/

jech- 2019- 213213

© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

AbsTrACT

background Mounting evidence from both experimental and epidemiological studies suggest that exposure to the endocrine disruptor bisphenol A (BPA) has a role in metabolic disorders. The aim of the present study was to assess whether urinary BPA concentrations were associated with dyslipidaemia in children (≤17 years old) and adults (≥18 years old) by performing a meta-analysis of data from six cycles (2003–2014) in the National Health and Nutrition Examination Survey (NHANES).

Methods We conducted a meta-analysis of data from 4604 children and 10 989 adult participants who were part of a substudy of urinary BPA measurements from six NHANES cycles from 2003 to 2014. Linear regression models conducted in each cycle were used to perform a meta-analysis to investigate associations between urinary BPA and serum levels of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), triglycerides (TG) and apolipoprotein B (ApoB).

results The meta-analysis did not disclose any significant associations between urinary BPA concentrations and LDL-C, HDL-C, TC, TG and ApoB in children. In adults, the meta-analysis revealed negative regression coefficients for all five lipid variables. However, no associations were significant following Bonferroni correction for multiple tests.

Conclusions In the present meta-analysis of cross- sectional data from NHANES, no associations were found between urinary BPA and the five different lipid variables when investigated in both children and adults.

However, considering the cross-sectional nature of the present study, results should be clarified in carefully designed longitudinal cohort studies with repeated BPA measurements.

InTroduCTIon

The ‘obesogen hypothesis’ and ‘metabolism-dis- rupting hypothesis’ suggest that exposure to endo- crine-disrupting chemicals (EDCs) found in the environment may predispose some individuals to the development of obesity and associated health conditions, such as type 2 diabetes and cardiovas- cular diseases. Bisphenol A (BPA) is one of the most commonly reported obesogens and metabolism-dis- rupting chemicals.

BPA is a high-volume chemical extensively used in epoxy resins lining in food and beverage containers and as a monomer in polycarbonate plastics in many consumer products. Its use is still abundant and environmental contamination is apparent in waters, sediments, soil, air, wildlife and humans.

Exposure

to BPA, primarily via food, but also through dental sealants, thermal paper (receipts and tickets), dermal exposure and inhalation of household dust, is evident from the detectable levels of urinary BPA in humans.

BPA has also been detected in adipose tissue,

and urinary BPA concentrations do not decline rapidly with fasting time, implying that BPA partly accumulates in adipose tissue and other tissue compartments.

BPA can interfere with multiple hormone actions,

including the activity of membrane and nuclear receptors (eg, oestrogen receptors), thyroid hormone receptor, androgen receptor and orphan receptors (eg, aryl hydrocarbon receptor). The diversity of plausible mechanisms of BPA, in addi- tion to the dose in relation to exposure during sensi- tive windows, may be an explanation for the effects of low-dose BPA exposure on endocrine systems.

In humans, BPA exposure has been associated with the metabolic syndrome

and its components hypertension,

diabetes mellitus,

insulin resis- tance

and obesity.

Especially troublesome is that associations between BPA exposure and meta- bolic diseases are observed also in children,

indicating that metabolic disturbances due to BPA exposure start at a young age.

Because of the intense focus on BPA, several studies using National Health and Nutrition Exam- ination Survey (NHANES) data to address the link between BPA and metabolic disorders such as obesity and diabetes already exist. However, to our knowledge, studies investigating the rela- tion between BPA exposure and dyslipidaemia are limited.

Thus, the aim of the present study was to investigate potential associations between urinary BPA concentrations and dyslipidaemia in US children and adults by performing a meta-anal- ysis of data from six NHANES cycles from 2003 to 2014. We hypothesised that urinary BPA, as a surrogate biomarker for BPA exposure, is associated with a disturbed lipid metabolism.

MeThods study population

NHANES is a continuous cross-sectional surveil- lance programme administered by the National Center for Health Statistics, which is part of Centers for Disease Control and Prevention (CDC). The aim of NHANES is to assess the health and nutritional status of the general US population for both children and adults. A detailed description of the NHANES study design and methods is available elsewhere.

Results in the present study are based on data from the

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Cycle 2003–2004 2005–2006 2007–2008 2009–2010 2011–2012 2013–2014

Characteristic N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD)

Age 852 12.33 (3.4) 896 12.13 (3.41) 690 11.25 (3.35) 727 11.09 (3.40) 689 11.02 (3.37) 750 11.2 (3.5)

Sex

Female 424 49.8% 429 47.9% 336 48.7% 349 48.0% 348 50.5% 375 50.0%

Male 428 50.2% 467 52.1% 354 51.3% 378 52.0% 341 49.5% 375 50.0%

Race/ethnicity

Mexican American 262 30.8% 307 34.3% 180 26.1% 199 27.4% 146 21.2% 180 24.0%

Other Hispanic 21 2.5% 21 2.3% 98 14.2% 95 13.1% 69 10.0% 75 10.0%

Non-Hispanic white 231 27.1% 246 27.5% 189 27.4% 236 32.4% 168 24.4% 191 25.5%

Non-Hispanic black 302 35.4% 268 29.9% 197 28.5% 146 20.1% 195 28.3% 191 25.5%

Other 36 4.2% 54 6.0% 26 3.8% 51 7.0% 111 16.1% 113 15.0%

Caregiver education

<9th grade 102 12.3% 112 13.0% 83 12.5% 78 11.0% 72 10.8% 75 10.3%

9–11th grade 177 21.4% 158 18.4% 138 20.9% 123 17.4% 118 17.7% 112 15.4%

High school or GED 197 23.9% 195 22.7% 157 23.7% 170 24.0% 150 22.6% 166 22.8%

Some college 227 27.5% 246 28.7% 176 26.6% 198 28.0% 177 26.6% 229 31.4%

College graduate or above

123 14.9% 148 17.2% 108 16.3% 139 19.6% 148 22.3% 147 20.1%

Smoking (serum cotinine (ng/mL))

778 6.7 (36.9) 780 9.0 (49.5) 597 3.9 (23.5) 628 3.6 (24.1) 585 3.9 (28.4) 643 1.95 (15.9)

No. of times/week you play or exercise hard

314 6.5 (5.8) 355 5.7 (2.9) 340 5.5 (2.3) 414 6.0 (1.9) 395 5.9 (1.8) 638 5.0 (2.3)

Caloric intake (kcal) 813 2190.2 (928.1) 843 2174.3 (1077.9) 660 1933.4 (778.7) 703 1965.9 (797.5) 639 1936.4 (734.1) 657 1944.7 (838.1)

Urinary BPA (ng/mL) 852 6.10 (9.06) 896 4.38 (7.59) 690 4.18 (9.01) 727 3.67 (10.36) 689 3.38 (9.89) 750 2.21 (2.85)

Urinary creatinine (µmol/L) 850 12 293.8 (7841.2) 896 12 543.3 (7236.3) 690 10 845.1 (6562.0) 727 10 564.4 (6521.3) 688 10 068.7 (6718.6) 750 10 780.4 (6822.6)

LDL-C (mmol/L) 350 2.31 (0.65) 239 2.20 (0.60) 112 2.29 (0.63) 128 2.36 (0.67) 146 2.22 (0.65) 149 2.17 (0.69)

HDL-C (mmol/L) 778 1.41 (0.33) 778 1.41 (0.33) 602 1.35 (0.33) 628 1.36 (0.34) 582 1.38 (0.31) 644 1.39 (0.34)

TC (mmol/L) 501 4.17 (0.77) 487 4.15 (0.71) 270 4.11 (0.76) 285 4.14 (0.76) 268 3.95 (0.75) 297 4.05 (0.77)

TG (mmol/L) 350 0.93 (0.50) 239 0.91 (0.44) 112 0.94 (0.49) 128 0.93 (0.53) 146 0.93 (0.59) 150 0.89 (0.64)

Apolipoprotein B (mg/dL) NA NA 241 72.9 (17.4) 112 69.6 (18.5) 128 71.2 (19.4) 147 65.7 (17.9) 150 65.9 (18.2)

BPA, bisphenol A; GED, general educational development; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NHANES, National Health and Nutrition Examination Survey; TC, total cholesterol; TG, triglycerides.

following six NHANES cycles containing BPA measurements:

NHANES 2003–2004, 2005–2006, 2007–2008, 2009–2010, 2011–2012 and 2013–2014. Data from the demographics, dietary, questionnaire, laboratory and physical examination components of each NHANES cycle were downloaded from the NHANES website https://www. cdc. gov/ nchs/ nhanes/

index. htm. For the present study, 4604 children, aged 6–17 years, and 10 989 adults, aged 18 years or older, with BPA measurement data in urine, were eligible.

urinary bPA

A spot urine sample was collected from a one-third random subset of participants of each NHANES cycle that were then analysed for BPA concentration. Total urinary BPA (free and conjugated; nanograms per millilitre) concentrations were measured using online solid-phase extraction coupled to high performance liquid chromatography-isotope dilution tandem mass spectrometry at the Division of Environmental Health Laboratory Sciences (National Center for Environ- mental Health, CDC). Comprehensive quality assurance and quality control was performed to ensure that samples were not contaminated during handling, storage and analysis.

Urinary creatinine was included in all multivariate models to correct for urinary dilution of BPA, as done in previous publications.

Lipid measures

Total cholesterol (TC), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) were analysed enzymatically in serum using spectrophotometric measurement of the colour of a reaction byproduct. The colour intensity is directly propor- tional to the concentration of the respective lipid. Low-density lipoprotein cholesterol (LDL-C) levels were calculated from measured values of TC, TG and HDL-C based on the Fried- wald equation ([LDL-C]=[TC]−[HDL-C]−[TG/5]), which is valid for individuals with TC levels <400 mg/dL.

Apoli- poprotein B (ApoB) was measured with an immunochemical light spectrometry method. Details of analyte extraction and measurement are available under each of the six different cycles under ‘Laboratory Methods’ at the NHANES website:

https://www. cdc. gov/ nchs/ nhanes/ index. htm.

demographic and lifestyle factors

Information on demographic and lifestyle factors of study participants was collected using standardised questionnaires.

Potential confounders were identified in the current liter- ature

and included after theoretical structured ordering of factors by use of directed acyclic graphs (online supplementary figure 1). Since obesity could have a big impact on lipid levels, we assumed the causal pathway to be: BPA exposure->obesity->dyslipidaemia. We therefore did not

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Table 2 Study population (adults) characteristics for the six different NHA NES cycles from 2003 to 2014 Cycle nh A nes 2003–2004 nh A nes 2005–2006 nh A nes 2007–2008 nh A nes 2009–2010 nh A nes 2011–2012 nh A nes 2013–2014 Characteristic N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) N Mean (SD) Age 1665 46.8 (20.7) 1652 44.8 (19.8) 1914 48.74 (18.6) 2022 47.18 (18.7) 1800 46.65 (18.5) 1936 47.62 (18.6) Sex Female 864 51.9% 849 51.4% 974 50.9% 1001 49.5% 882 49.0% 1026 53.0% Male 801 48.1% 803 48.6% 940 49.1% 1021 50.5% 918 51.0% 910 47.0% Race/ethnicity Mexican American 351 21.1% 330 20.0 351 18.3% 367 18.1% 170 9.5% 258 13.3% Other Hispanic 61 3.7% 51 3.1 204 10.7% 198 9.8% 186 10.3% 177 9.1% Non-Hispanic white 844 50.7% 792 47.9 888 46.4% 970 48.0% 645 35.8% 797 41.2% Non-Hispanic black 333 20.0% 410 24.8 400 20.9% 370 18.3% 470 26.1% 418 21.6% Other 76 4.5% 69 4.2 71 3.7% 117 5.8% 329 18.3% 286 14.8% Education <9th grade 215 14.5% 165 11.1% 237 13.1% 239 12.5% 169 9.9% 144 8.0% 9-11th grade 219 14.7% 226 15.2% 302 16.6% 307 16.1% 234 13.8% 287 15.8% High school or GED 362 24.4% 365 24.5% 468 25.8% 459 24.0% 336 19.7% 408 22.5% Some college 397 26.7% 428 28.8% 464 25.6% 508 26.6% 518 30.4% 534 29.4% College graduate or above 292 19.7% 304 20.4% 343 18.9% 397 20.8% 446 26.2% 440 24.3% Smoking (serum cotinine (ng/mL)) 1581 56.4 (133.6) 1561 60.1 (129.4) 1811 64.0 (137.8) 1925 58.3 (123.6) 1694 49.7 (122.3) 1870 57.6 (127.0) Vigorous activity over past 30 days Ye s 489 29.4% 600 36.3% 403 21.1% 407 20.1% 435 24.2% 437 22.6% No 1176 70.6% 1052 63.7% 1511 78.9% 1615 79.9% 1365 75.8% 1499 77.4% Caloric intak e (kcal) 1584 2199.5 (1021.0) 1591 2194.5 (1009.5) 1824 2064.0 (1057.9) 1934 2125.7 (994.3) 1642 2169.0 (1026.8) 1766 2121.5 (1068.2) Now taking statins Ye s 212 12.7% 212 12.8% 342 17.9% 350 17.3% 330 18.3% 372 19.2% No 1453 87.3% 1440 87.2% 1572 82.1% 1672 82.7% 1470 81.7% 1564 80.8% Urinary BP A (ng/mL) 1665 4.69 (6.72) 1652 4.03 (12.70) 1914 3.67 (6.73) 2022 4.89 (30.01) 1800 3.10 (7.76) 1936 2.97 (18.94) Urinary creatinine (µmol/L) 1664 11 953.7 (7527.5) 1652 134.38 (81.11) 1914 124.72 (78.07) 2022 111 263.0 (7039.9) 1799 10 694.6 (7209.9) 1934 11 451.0 (7389.3) LDL-C (mmol/L) 733 2.98 (0.94) 732 2.88 (0.96) 862 2.89 (0.86) 920 2.91 (0.87) 808 2.95 (0.90) 920 2.84 (0.93) HDL-C (mmol/L) 1583 1.41 (0.43) 1561 1.43 (0.43) 1811 1.34 (0.41) 1922 1.35 (0.41) 1687 1.36 (0.38) 1868 1.36 (0.41) TC (mmol/L) 1572 5.19 (1.15) 1554 5.09 (1.15) 1803 5.06 (1.07) 1919 4.95 (1.06) 1681 4.89 (1.05) 1863 4.89 (1.06) TG (mmol/L) 752 1.67 (1.38) 749 1.59 (1.39) 875 1.49 (1.19) 937 1.47 (1.17) 823 1.39 (1.08) 930 1.32 (0.90) Apolipoprotein B (mg/dL) NA NA 752 99.5 (29.3) 874 91.2 (24.0) 937 90.1 (24.1) 823 88.6 (24.6) 930 89.3 (25.8) ApoB , apolipoprotein B; BP A, bisphenol A;GED , general educational development; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol;NHANES , National Health and Nutrition Examination Survey; TC, total cholesterol; TG , triglycerides . BIBSAM Consortia. Protected by copyright. on December 5, 2019 at Uppsala Universitet http://jech.bmj.com/

Table 3 Meta-analysis results of associations between urinary BPA and five different lipids in children and adults, when analysing women and men together using linear regression models

standard adjusted model* Fully adjusted model†

β 95% CI P value β 95% CI P value

Children

LDL-C −0.005 −0.05 to 0.05 0.98 0.003 −0.05 to 0.05 0.91

HDL-C −0.01 −0.02 to 0.002 0.09 −0.01 −0.02 to 0.002 0.10

TC 0.008 −0.03 to 0.05 0.70 0.01 −0.03 to 0.05 0.62

TG 0.01 −0.02 to 0.05 0.51 0.01 −0.02 to 0.05 0.48

ApoB −0.48 −2.1 to 1.2 0.57 −0.54 −2.3 to 1.2 0.54

Adults

LDL-C −0.02 −0.05 to 0.01 0.22 −0.02 −0.05 to 0.01 0.23

HDL-C −0.01 −0.02 to 0.001 0.025 −0.006 −0.01 to 0.003 0.18

TC −0.02 −0.04 to 0.004 0.11 −0.02 −0.01 to 0.003 0.09

TG −0.01 −0.03 to 0.006 0.19 −0.02 −0.03 to 0.0002 0.053

ApoB −0.89 −1.8 to 0.06 0.066 −0.91 −1.8-(−0.02) 0.044

*Adjusted for urinary creatinine, age, sex and race.

†Adjusted for urinary creatinine, sex, age, race, education/caregiver education, smoking (serum cotinine), income to poverty ratio, physical activity, alcohol intake (adults only), caloric intake, statins (adults only) and pregnancy (adults only).

ApoB, apolipoprotein B; BPA, bisphenol A; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides.

disturbances, that is, obesity is regarded as an intermediate in the present study. Sex was categorised as male or female. Race/

ethnicity was categorised into five groups: Mexican American, other Hispanic, non-Hispanic white, non-Hispanic black and other. Self-reported education/caregiver educational attain- ment was categorised into four levels: <9th grade, 9–11th grade, high school or general educational development and some college. Smoking was characterised using serum cotinine, a major metabolite of nicotine that is used as a marker for both active smoking and as an index of environmental tobacco smoke exposure or ‘passive smoking’. Income-to-poverty ratio is a continuous measure calculated using the Department of Health and Human Services poverty guidelines. For children, physical activity was characterised as the number of times per week the participant play or exercise hard. For adults, physical activity was categorised as having performed vigorous activity during the past 30 days or not. Statins was characterised as currently taking prescribed medicine (adults only). Alcohol intake was characterised as how often the participants (adults only) have drunk alcohol over past 12 months. Energy intake was obtained as mean total caloric intake (kcal) per day.

statistical analysis

Separate analyses were performed for adults (≥18 years old) and children (≤17 years old), which is the most commonly used approach in this type of study. The reason for this is that the children were likely more or less exposed even before birth, while the adults at different ages would be very hetero- geneous in that respect.

Due to a right-skewed distribution, urinary BPA concentra- tions, TG and urinary creatinine were log-transformed. Linear regression analysis was performed with the lipid variables (LDL-C, HDL-C, TC, TG and ApoB) as dependent variables in separate models for each lipid variable and with BPA as the main independent variable.

In the first set of models, adjustment was performed for age, sex, urinary creatinine and race. In the second set of models, we also included other a priori chosen confounders because of

income-to-poverty ratio, physical activity, alcohol intake (adults only), caloric intake, statins (adults only) and preg- nancy (adults only). In a third set of models, an interaction term between sex and BPA was included to evaluate possible sex differences. In a fourth set of models, a squared term was included for BPA to evaluate possible non-linear relationships.

Missing data on education, alcohol intake, smoking (serum cotinine), statin use, physical activity and energy intake were imputed by using multiple imputation (Markov-Chain Monte Carlo) with 20 imputations. Each examination cycle was anal- ysed separately and the results from all examination cycles were meta-analysed using the inverse-variance weighted fixed effect technique.

A sensitivity analysis was performed by excluding all indi- viduals taking statins. A Bonferroni adjustment was used to account for multiple testing (critical level of significance (0.05/10)=0.005). STATA V.15 was used for calculations.

resuLTs

During the study period (2003–2014), 25 172 children (<18 years of age) and 35 915 adults (>18 years of age) participated in NHANES. Our analytic sample comprised the 4604 children and 10 989 adult participants randomly selected for measure- ment of urinary BPA concentrations. Tables 1 and 2 present descriptive basic characteristics for children and adults of each of the six different NHANES cycles from 2003 to 2014. Over the whole study period, the mean levels of urinary BPA varied from 2.21 ng/mL to 6.10 ng/mL in children and from 2.97 ng/

mL to 4.89 ng/mL in adults. For children, mean urinary BPA levels were highest in the 2003–2004 examination cycle and then decreased over time, with the lowest mean value for the 2013–2014 cycle. For adults, no such pattern was seen.

In children, the meta-analysis showed negative associations between urinary BPA concentrations and ApoB, LDL-C and HDL-C, and positive associations for TC and TG, in models adjusting for age, sex, race and urinary creatinine (table 3). In adults, the meta-analysis showed negative associations between urinary BPA concentrations and all five evaluated lipid variables

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Figure 1 Results of the meta-analysis of the relationship between urinary BPA and five different lipid variables in adult participants in models adjusting for age, sex, race and urinary creatinine. The estimates and 95% CI are given (right side of each figure) for each of the six NHANES examination cycles (specified in the left side of each figure) together with a summarised estimate. ApoB was not measured in the first two NHANES examination cycles. ApoB, apolipoprotein B; BPA, bisphenol A; HDL, high-density lipoprotein; LDL, low-density lipoprotein; NHANES, National Health and Nutrition Examination Survey.

(figure 1, table 3). However, none of the investigated associations were significant following Bonferroni adjustment (p>0.005), either in children or in adults. Following further adjustment for systolic blood pressure and fasting glucose to the standard adjusted model in adults the relationships between BPA and lipids were generally attenuated, as can be seen in online supplemental table 1.

Further adjustment for lifestyle factors changed the above-mentioned associations only marginally (table 3).

However, again, none of the associations were significant

following Bonferroni adjustment (p>0.005). Including a squared term for BPA in the models did not disclose any signif- icant non-linear relationships, either in children or in adults.

Neither did the sensitivity analysis, by excluding individuals taking statins, result in any significant relationships.

Including an interaction term between sex and BPA in the models, to evaluate possible sex differences, did not disclose any sex interactions with a statistical value of p<0.005 for any of the lipids in either children or adults (table 4).

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What is already known on this subject

► It has become evident from experimental animal studies that the endocrine disrupting chemical bisphenol A (BPA) also can act as a metabolism disrupting chemical, that is, that it can interfere with different metabolic processes that can increase the individual’s susceptibility to metabolic disease. This is, however, not as clear from reports from epidemiological studies, where both negative and positive associations have been reported between urinary BPA and metabolic diseases, mainly obesity.

What this study adds

► In the present study, we have performed a comprehensive meta-analysis using data from six National Health and Nutrition Examination (NHANES) cycles (children: n=4604 and adults: n=10 989) to investigate associations between urinary BPA exposure and serum lipids. Our hypothesis was that urinary BPA would be associated with dyslipidaemia since previous studies using NHANES data have reported associations between urinary BPA and obesity and diabetes.

Despite these earlier reported associations, we could not find any associations between BPA and dyslipidaemia in the present meta-analysis of this particular cohort. However, the earlier studies have only used some NHANES cycles compared with our meta-analysis where we have included six NHANES cycles which, of course, result in a larger investigated population. It could be that only a few cycles stand out and drive the positive associations found in the earlier studies. BPA is a confirmed endocrine-disrupting chemical, and it is quite evident from the literature that it can also disturb lipid metabolism, especially from experimental animal studies; therefore, we believe that there is a true association between BPA and obesity, diabetes and dyslipidaemia, but there is a need for better well-planned cohort studies in order to truly confirm these associations.

Our conclusion is therefore that despite the large sample size of the present meta-analysis and the thorough statistical analysis performed, there are no associations between BPA and dyslipidaemia in the particular cohort investigated (NHANES). It is important that the design of future studies are longitudinal and include several BPA measurements in order to make the exposure more representative of the real life scenario. It is especially important to acquire repeated measures of endocrine disrupting chemicals with a short half- life, such as bisphenols.

Female Male Interaction term

β 95% CI P value β 95% CI P value P value

Children

LDL-C 0.04 −0.04 to 0.11 0.32 −0.03 −0.09 to 0.04 0.40 0.36

HDL-C −0.01 −0.03 to 0.007 0.22 −0.01 −0.03 to 0.003 0.10 0.57

TC −0.02 −0.08 to 0.04 0.49 0.02 −0.04 to 0.07 0.55 0.38

TG −0.02 −0.07 to 0.03 0.44 0.04 −0.003 to 0.09 0.07 0.13

ApoB −0.18 −2.9 to 2.6 0.90 −0.72 −2.8 to 1.4 0.50 0.90

Adults

LDL-C −0.01 −0.05 to 0.03 0.56 −0.02 −0.07 to 0.02 0.27 0.27

HDL-C −0.01 −0.03 to 0.0002 0.053 −0.008 −0.02 to 0.004 0.18 0.061

TC −0.02 −0.05 to 0.02 0.30 −0.02 −0.05 to 0.01 0.23 0.12

TG −0.01 −0.04 to 0.01 0.37 −0.01 −0.04 to 0.02 0.46 0.37

ApoB −0.98 −2.3 to 0.4 0.16 −0.66 −1.9 to 0.6 0.32 0.79

ApoB, apolipoprotein B; BPA, bisphenol A; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; TC, total cholesterol; TG, triglycerides.

dIsCussIon

In the present study, we aimed to assess whether urinary BPA concentrations were associated with dyslipidaemia by performing a meta-analysis of data on children and adults that participated in the 2003–2014 NHANES, as we have previ- ously reported altered blood lipids after developmental expo- sure to BPA in rats.

The present study did not reveal any major associations between urinary BPA levels and dyslipidaemia in children or adults despite the large sample sizes achieved by the meta-analysis performed using several examination cycles of NHANES data. In adults, we found a consistent pattern of an inverse relationship between BPA and all five investigated lipids, but none of the associations were significant following Bonferroni adjustment.

Two previous studies have used NHANES data to investigate the relationship between BPA exposure and lipid levels. In a study of adults, no significant relationships between urinary BPA and serum LDL-C or TG were found.

However, that study used only the first (2003–2004) examination cycle and might therefore have limited power to detect any signif- icant associations. In another study performed in children, no significant relationships between urinary BPA and serum TC, HDL-C, LDL-C or TG were observed.

That study used pooled data from all NHANES examinations performed from 2003 to 2010. Our data are in agreement with those two studies, but in our case, we had better power to detect any potential relationships. Especially in the adults (n>10 000), we had the power to detect relationships for which the varia- tion in BPA levels explained <0.05% of the variation in lipid

levels. Such relationships would be statistically significant but would be of doubtful clinical significance.

Several previous studies that have used data from some NHANES cycles have found a positive association between BPA exposure and obesity in both children

and adults,

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and diabetes in adults,

whereas we did not find any associations between BPA and dyslipidaemia in the present meta-analysis. However, the earlier studies have only used some NHANES cycles compared with our meta-analysis where we have included six NHANES cycles, which of course result in a larger investigated population. It could be that only a few cycles stand out and drive the positive associations found in the earlier studies. BPA is a confirmed endocrine disrupting chemical, and it is quite evident from the literature that it can also disturb lipid metabolism, especially from experimental animal studies; therefore, we believe that there is a true asso- ciation between BPA and obesity, diabetes and dyslipidaemia, but there is a need for better well-planned cohort studies in order to truly confirm these associations. In addition, when it comes to the relation between BPA exposure and obesity in particular, it is not possible to rule out the possibility that obese individuals ingest food with higher BPA content or have greater adipose stores of BPA.

A review evaluating epidemiological studies on BPA and cardiometabolic health outcomes showed that nearly all used a cross-sectional design and relied on a single measure of BPA exposure, which may result in serious exposure misclassifi- cation. In addition, the result of the review could conclude that for all outcomes, results across studies were inconsis- tent.

Factors underlying the differing results observed among studies are multifactorial and likely the result of differences in study protocol, unaccounted for confounding factors or reverse causality (eg, individuals who are obese have a different dietary pattern that increases their exposure risk).

Previous studies conducted on data from NHANES often use pooled data from different survey cycles. It has been shown, in the context of correlation analysis, that pooling can generate false-positive findings and also that effects that do exist within the subgroups can be concealed.

In the present study, we chose to handle each cycle as a different study population and thereafter performing a meta-analysis to avoid those pitfalls.

In our standard model, we adjusted for age, sex, race and urinary creatinine. Further adjustment for systolic blood pres- sure and fasting glucose generally attenuated the relationships between BPA and the lipids in the adults (online supplemen- tary table 1). Both blood pressure and glucose are related to lipid levels, but it is not known if these two major risk factors could affect BPA levels by means of changing the metabo- lism or absorption of BPA. Therefore, it is not clear if blood pressure or glucose are confounders or mediators in the BPA versus lipid relationship, as BPA has been linked to diabetes and hypertension.

The major strength of this study is the large meta-anal- ysis of a nationally representative sample with high-quality measurements of BPA. Moreover, the use of rigorous study methods to collect the data and the availability of extensive data on confounders further strengthen the study. However, given the cross-sectional design, it is not possible to rule out reverse causality. Another major limitation is the reliance of a single spot urine sample to characterise BPA exposure and the unavailability of BPA measurements on children younger than 6 years of age. It is especially important to acquire repeated measures of EDCs with a short half-life, such as bisphenols.

Thus, in future studies, BPA levels need to be measured at more than one time point to truly reflect BPA exposure.

Also, in epidemiological studies, it is difficult to assess asso- ciations between low exposure levels and outcomes. Instead, it is increasing levels that are investigated with regard to different association outcomes. In addition, epidemiological

studies fail to consider exposure relative to critical periods of differentiation (susceptibility windows), which has been iden- tified as especially important for EDCs. Another limitation of the study is that Tanner stage was not assessed for children enrolled in NHANES. Therefore, we were unable to account for the potential impact of puberty on lipid concentrations in our analyses. However, all regression models were adjusted for children’s age, which is a significant predictor of onset of puberty.

ConCLusIons

Despite the large sample size of the present meta-analysis and the thorough statistical analysis performed, no associations were found between urinary BPA levels and the five different lipid variables investigated in children and adults. However, considering the cross-sectional nature of the present study and earlier studies showing associations between BPA and obesity and diabetes, these results should be clarified in care- fully designed longitudinal cohort studies with repeated BPA measurements. It is especially important to acquire repeated measures of endocrine disrupting chemicals with a short half- life, such as bisphenols.

Contributors LD and LL conceived the project, planned and performed the statistical analyses. LD wrote the initial draft of the manuscript and revised the manuscript. All authors discussed the results, read and contributed to the final manuscript.

Funding This work was supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning, FORMAS (grant number 216-2012-475) and by research funding from Uppsala University Hospital (ALF).

Competing interests None declared.

Patient consent for publication Not required.

ethics approval and consent to participate National Health and Nutrition Examination Survey (NHANES) is a publicly available data set and all participants in NHANES provide written informed consent, consistent with approval from the National Center for Health Statistics Research Ethics Review Board (NCHS ERB) (protocol #98-12 for NHANES cycle 2003-2004, protocol #2005-06 for NHANES cycles 2005-2006, 2007-2008 and 2009-2010, protocol #2011-17 for NHANES cycles 2011-2012 and 2013-2014).

Provenance and peer review Not commissioned; externally peer reviewed.

data availability statement The datasets used and analysed during the current study are available in the NHANES repository (https://www. cdc. gov/ nchs/ nhanes/

index. htm).

open access This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http:// creativecommons. org/ licenses/ by- nc/ 4. 0/.

RefeRences

1 Grün F, Blumberg B. Endocrine disrupters as obesogens. Mol Cell Endocrinol 2009;304:19–29.

2 Heindel JJ, Blumberg B, Cave M, et al. Metabolism disrupting chemicals and metabolic disorders. Reprod Toxicol 2017;68:3–33.

3 Corrales J, Kristofco LA, Steele WB, et al. Global assessment of bisphenol A in the environment: review and analysis of its occurrence and bioaccumulation. Dose Response 2015;13.

4 Calafat AM, Kuklenyik Z, Reidy JA, et al. Urinary concentrations of bisphenol A and 4-nonylphenol in a human reference population. Environ Health Perspect 2005;113:391–5.

5 Calafat AM, Ye X, Wong L-Y, et al. Exposure of the U.S. Population to Bisphenol A and 4-tertiary-octylphenol: 2003-2004. Environ Health Perspect 2008;116:39–44.

6 Vandenberg LN, Hauser R, Marcus M, et al. Human exposure to bisphenol A (BPA).

Reprod Toxicol 2007;24:139–77.

BIBSAM Consortia. Protected by copyright. on December 5, 2019 at Uppsala Universitet http://jech.bmj.com/

8 Chen Y, Fang J, Ren L, et al. Urinary bisphenol analogues and triclosan in children from South China and implications for human exposure. Environ Pollut 2018;238:299–305.

9 Fernandez MF, Arrebola JP, Taoufiki J, et al. Bisphenol-A and chlorinated derivatives in adipose tissue of women. Reprod Toxicol 2007;24:259–64.

10 Stahlhut RW, Welshons WV, Swan SH. Bisphenol a data in NHANES suggest longer than expected half-life, substantial nonfood exposure, or both. Environ Health Perspect 2009;117:784–9.

11 Csanády GA, Oberste-Frielinghaus HR, Semder B, et al. Distribution and unspecific protein binding of the xenoestrogens bisphenol A and daidzein. Arch Toxicol 2002;76:299–305.

12 Reif DM, Martin MT, Tan SW, et al. Endocrine profiling and prioritization of environmental chemicals using ToxCast data. Environ Health Perspect 2010;118:1714–20.

13 Acconcia F, Pallottini V, Marino M. Molecular mechanisms of action of BPA. Dose Response 2015;13.

14 Teppala S, Madhavan S, Shankar A. Bisphenol A and metabolic syndrome: results from NHANES. Int J Endocrinol 2012;2012:598180

15 Bae S, Kim JH, Lim Y-H, et al. Associations of bisphenol a exposure with heart rate variability and blood pressure. Hypertension 2012;60:786–93.

16 Lang IA, Galloway TS, Scarlett A, et al. Association of urinary bisphenol a concentration with medical disorders and laboratory abnormalities in adults. JAMA 2008;300:1303–10.

17 Shankar A, Teppala S. Relationship between urinary bisphenol A levels and diabetes mellitus. J Clin Endocrinol Metab 2011;96:3822–6.

18 Wang T, Li M, Chen B, et al. Urinary bisphenol A (BPA) concentration associates with obesity and insulin resistance. J Clin Endocrinol Metab 2012;97:E223–E227.

19 Carwile JL, Michels KB. Urinary bisphenol A and obesity: NHANES 2003-2006. Environ Res 2011;111:825–30.

20 Trasande L, Attina TM, Blustein J. Association between urinary bisphenol a concentration and obesity prevalence in children and adolescents. JAMA 2012;308:1113–21.

Epidemiol 2013;177:1263–70.

23 Eng DS, Lee JM, Gebremariam A, et al. Bisphenol A and chronic disease risk factors in US children. Pediatrics 2013;132:e637–45.

24 Johnson CL P-RR, Ogden CL. The National health and nutrition examination survey:

Analytic guidelines 1999-2010. Hyattsville, Maryland, 2013.

25 Barr DB, Wilder LC, Caudill SP, et al. Urinary creatinine concentrations in the U.S.

population: implications for urinary biologic monitoring measurements. Environ Health Perspect 2005;113:192–200.

26 Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972;18:499–502.

27 Verstraete SG, Wojcicki JM, Perito ER, et al. Bisphenol A increases risk for presumed non-alcoholic fatty liver disease in Hispanic adolescents in NHANES 2003-2010. Environ Health 2018;17.

28 Wells EM, Jackson LW, Koontz MB. Association between bisphenol A and waist- to-height ratio among children: National health and nutrition examination survey, 2003-2010. Ann Epidemiol 2014;24:165–7.

29 Lejonklou MH, Dunder L, Bladin E, et al. Effects of low-dose developmental bisphenol a exposure on metabolic parameters and gene expression in male and female Fischer 344 rat offspring. Environ Health Perspect 2017;125:067018.

30 Sabanayagam C, Teppala S, Shankar A. Relationship between urinary bisphenol A levels and prediabetes among subjects free of diabetes. Acta Diabetol 2013;50:625–31.

31 Silver MK, O’Neill MS, Sowers MR, et al. Urinary bisphenol A and type-2 diabetes in U.S. adults: data from NHANES 2003-2008. PLoS One 2011;6:e26868.

32 Lakind JS, Goodman M, Mattison DR. Bisphenol A and indicators of obesity, glucose metabolism/type 2 diabetes and cardiovascular disease: a systematic review of epidemiologic research. Crit Rev Toxicol 2014;44:121–50.

33 Bravata DM, Olkin I. Simple pooling versus combining in meta-analysis. Eval Health Prof 2001;24:218–30.

BIBSAM Consortia. Protected by copyright. on December 5, 2019 at Uppsala Universitet http://jech.bmj.com/